Purpose

The purpose of this research is to provide a theoretical framework for complex equipment quality risk evaluation. The primary aim of the framework is to enhance the ability to identify risks and improve risk control efficiency during the development phase.

Design/methodology/approach

A novel framework for quality risk evaluation in complex equipment is proposed, which integrates probabilistic hesitant fuzzy set-quality function deployment (PHFS-QFD) and grey clustering. PHFS-QFD is applied to identify the quality risk factors, and grey clustering is used to evaluate quality risks in cases of poor quality information during the development stage. The unfolding function of QFD is applied to simplify complex evaluation problems.

Findings

The methodology presents an innovative approach to quality risk evaluation for complex equipment development. The case analysis demonstrates that this method can efficiently evaluate the quality risks for aircraft development and systematically trace back the risk factors through hierarchical relationships. In comparison to traditional failure mode and effects analysis methods for quality risk assessment, this approach exhibits superior effectiveness and reliability in managing quality risks for complex equipment development.

Originality/value

This study contributes to the field by introducing a novel theoretical framework that combines PHFS-QFD and grey clustering. The integration of these approaches significantly improves the quality risk evaluation process for complex equipment development, overcoming challenges related to data scarcity and simplifying the assessment of intricate systems.

中文翻译：

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一种融合PHFS-QFD和灰色聚类的复杂装备开发质量风险评估框架

目的

本研究的目的是为复杂设备质量风险评估提供理论框架。该框架的首要目的是增强开发阶段的风险识别能力，提高风险控制效率。

设计/方法论/途径

提出了一种集成概率犹豫模糊集质量函数部署（PHFS-QFD）和灰色聚类的复杂设备质量风险评估新框架。采用PHFS-QFD识别质量风险因素，在开发阶段信息质量较差的情况下，采用灰色聚类评估质量风险。QFD的展开功能被用来简化复杂的评估问题。

发现

该方法提出了复杂设备开发质量风险评估的创新方法。案例分析表明，该方法能够有效评估飞机研制的质量风险，并通过层次关系系统地追溯风险因素。与传统的质量风险评估的失效模式和影响分析方法相比，该方法在管理复杂设备开发的质量风险方面表现出卓越的有效性和可靠性。

原创性/价值

这项研究通过引入结合 PHFS-QFD 和灰色聚类的新颖理论框架对该领域做出了贡献。这些方法的集成显着改进了复杂设备开发的质量风险评估流程，克服了与数据稀缺相关的挑战并简化了复杂系统的评估。